## Vector Autoregression

The vector autoregression model (VAR) is actually a little simpler to estimate than the VEC model. It is used when there is no cointegration among the variables and it is estimated using time-series that have been transformed to their stationary values.

In the example from POE4, we have macroeconomic data on RPDI and RPCE for the United States. The data are found in the fred. gdt dataset and have already been transformed into their natural logarithms. In the dataset, y is the log of real disposable income and c is log of real consumption expenditures. As in the previous example, the first step is to determine whether the variables are stationary. If they are not, then you transform them into stationary time-series and test for cointegration.

The data need to be analyzed in the same way as ...

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